Geographical Information System (GIS)-based maps for monitoring of entomological risk factors affecting transmission of chikungunya in Sri Lanka

Transcription

1 Geographical Information System (GIS)-based maps for monitoring of entomological risk factors affecting transmission of chikungunya in Sri Lanka M.D. Hapugoda 1, N.K. Gunewardena 1, P.H.D. Kusumawathie 2, G.A.J.S.K. Jayasooriya 2, H.C. Hapuarachchi 1 and W. Abeyewickreme 1 1 Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka 2 Anti-Malaria Campaign, Kandy, Sri Lanka 1

2 INTRODUCTION Chikungunya fever is a viral disease transmitted to humans by the bite of infected mosquitoes. Chikungunya virus is a member of the genus Alphavirus, in the family Togaviridae. This virus is spread by Aedes aegypti and Aedes albopictus mosquitoes. 2

3 Introduction cont. Chikungunya virus was first isolated from the blood of a febrile patient in Tanzania in 1953, and has since been identified repeatedly in west, central and southern Africa and many areas of Asia. The disease has been cited as the cause of numerous human epidemics in those areas since that time. Most recent outbreaks have been reported from India and various Indian Ocean islands including Sri Lanka. 3

4 Introduction cont. At present, chikungunya is an important disease in Sri Lanka. Chikungunya remains very much a neglected disease and a public health issue, and clearly, there is an urgent need to study on possible risk factors affecting transmission of the disease to bridge the gap of knowledge concerning this pathogen. Possible risk factors- entomological epidemiological environmental socio-economic knowledge attitude and practices of human 4

5 OBJICTIVE To monitor entomological risk factors affecting transmission of chikungunya using GIS mapping. 5

6 RESEARCH DESIGN Entomological risk factors affecting transmission of chikungunya were examined in a selected chikungunya hotspot in Sri Lanka from April to July in

7 Research design cont. Study area Study area was situated in the District of Kandy, in the central part of the island. Kandy Municipal Council area was selected. the latitude of N the longitude of E 7

8 Research design cont. Map1. Sri Lanka showing the study area 8

9 Research design cont. Study population Ninety nine house-holds in 33 clusters were recruited. The distant between clusters was at least 200 m which is beyond the maximum flight range of Aedes mosquitoes. 3 house-holds/cluster 99 house-holds/33 clusters 9

10 Research design cont. Collection of data Position of each house was recorded using a Global Position System (GPS) receiver. Monthly surveillance was conducted using standard entomological surveillance methods followed by obtaining information through a pre-tested questionnaire. Adults - Human landing diurnal collection technique Larvae - Normal larval surveillance technique 10

11 Research design cont. Analysis and presenting data Monthly cluster index for the presence of Aedes vectors in each cluster was calculated. Cluster index = No of positive clusters X 100 No of clusters examined Cluster index for each species was indicated in each map. 66% 33% 0% 11

12 Research design cont. Monthly container index for each cluster was calculated. Container index = No of positive containers X 100 Total no of containers in a cluster Container index for each species was indicated in each map. 66% 33% 0% 12

13 Research design cont. GIS was used to display 1. Spatial distribution of selected house-holds and clusters; GPS readings of each house-hold were overlaid n digital land used maps using GIS and presented all house-holds and clusters on GIS-based maps. 2. Spatial and temporal distribution of vectors; Monthly cluster index for each vector species was overlaid on GIS-based maps. 3. Spatial and temporal distribution of key breeding sites; Monthly container index was overlaid on GIS-based maps. 13

14 RESULTS Spatial distribution of selected house-holds and clusters DEN1 Major land use pattern of the selected area was human dwellings. 14

15 Map 2. Spatial distribution of selected clusters Results cont. 15

16 Map 3. Spatial distribution of selected clusters Results cont. 16

17 Map 4. Spatial distribution of all 33 clusters Results cont. 17

18 Results cont. Spatial and temporal distribution of vectors Presence of high density/cluster index of Ae. albopictus mosquitoes was observed in all clusters throughout the study period. 18

19 Results cont. Map 5. Spatial and temporal distribution of vector mosquitoes Cluster index for Aedes, June, % Ae.a lar 33% Ae.a lar 66% Ae.al ad 33% Ae.al ad 66% Ae.ae lar 33% Ae.ae lar 19

20 Spatial and temporal distribution of key breeding sites Results cont. Presence of Ae. albopictus mosquitoes in more than 90% of the key (artificial) breeding habitats was observed in all clusters throughout the study period. 20

21 Results cont. Map 6. Spatial and temporal distribution of vector breeding sites Container index, June, %Ae.a larvae 33%Ae.a larvae 66%Ae.ae larvae 33%Ae.ae larvae 66% All possible 33% All possible 21

22 CONCLUSIONS Generalized high density of Ae. albopictus suggests that this species may play a major role in transmitting chikungunya in the study area. GIS-based maps may be used as an important tool to find out spatial and temporal distribution of vectors and key breeding sites in a selected hotspot, which would enable cost effective and efficient interventions for vector control in disease endemic areas. 22

23 Discussion cont. Further, information regarding long term surveillance activities conducted in a chikungunya risk area can be manipulated and presented using tools of GIS. This is important to predict impending epidemics in order to use limited resources in a cost effective and efficient manner to control the epidemics. 23

24 THANK YOU 24